Feasibility Study
Feasibility studies rigorously assess the viability of novel approaches or technologies across diverse scientific domains, ranging from medical diagnostics and data sharing to robotics and environmental monitoring. Current research emphasizes the application of machine learning models, including deep neural networks (DNNs), convolutional neural networks (CNNs), and transformer architectures, to improve accuracy, efficiency, and data handling in these studies. These investigations are crucial for guiding resource allocation, informing decision-making, and ultimately translating promising scientific advancements into practical applications and improved outcomes across various fields.
Papers
October 4, 2024
July 19, 2024
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November 11, 2023
November 1, 2023
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February 27, 2023
December 5, 2022
November 26, 2022
October 6, 2022